Distribution System Voltage Management and Optimization for Integration of Renewables and Electric Vehicles: Research Gap Analysis

California is striving to achieve 33% renewable penetration by 2020 in accordance with the state’s Renewable Portfolio Standard (RPS). The behavior of renewable resources and electric vehicles in distribution systems is creating constraints on the penetration of these resources into the distribution system. One such constraint is the ability of present-­‐‑day voltage management methodologies to maintain proper distribution system voltage profiles in the face of higher penetrations of PV and electric vehicle technologies. This white paper describes the research gaps that have been identified in current Volt/VAR Optimization and Control (VVOC) technologies, the emerging technologies which are becoming available for use in VVOC, and the research gaps which exist and must be overcome in order to realize the full promise of these emerging technologies

Green Principles, Parametric Analysis, and Optimization for Guiding Environmental and Economic Performance of Grid-scale Energy Storage Systems

The development and deployment of grid-scale energy storage technologies have increased recently and are expected to grow due to technology improvements and supporting policies. While energy storage can help increase the penetration of renewables, reduce the consumption of fossil fuels, and increase the grid sustainability, its integration into the electric grid poses unique sustainability challenges that need to be investigated through systematic sustainability assessment frameworks. The main objective of this dissertation is to develop principles and models to assess the environmental and economic impacts of grid-scale energy storage and guide its development and deployment. The first study of this dissertation is an initial case study of energy storage to examine the role of cost-effective energy storage in supporting high penetration of wind energy and achieving emissions targets in an off-grid configuration. In this study, the micro-grid system includes wind energy integrated with vanadium redox flow battery (VRFB) as energy storage, and natural gas engine. Life cycle greenhouse gas (GHG) emissions and total cost of delivered electricity are evaluated and generation mixes are optimized to meet emissions targets at the minimum cost. The results demonstrate that while incorporating energy storage consistently reduces life cycle GHG emissions in the system by integrating more wind energy, its integration is cost-effective only under very ambitious emission targets. The insights from this case study and additional literature review led to the development of a set of twelve principles for green energy storage, presented in the second study. These principles are applicable to the wide range of energy storage technologies and grid applications, and are developed to guide the design, maintenance, and operation of energy storage systems for grid applications. The robustness of principles was tested through a comprehensive literature review and also through in-depth quantitative analyses of the VRFB off-grid system. An in-depth parametric analysis is developed in the third study to evaluate the impacts of six key parameters (e.g. energy storage service-life) that influence the environmental performance of six energy storage technologies within three specific grid applications (including time-shifting, frequency regulation, and power reliability). This study reveals that round-trip efficiency and heat rate of charging and displaced generation technologies are dominant parameters in time-shifting and regulation applications, whereas energy storage service life and production burden dominate in power reliability. Finally, an optimization model is developed in the fourth study to examine the real-world application of energy storage in bulk energy time-shifting in California grid under varying renewable penetration levels. The objective was to find the optimal operation and size of energy storage in order to minimize the system total costs (including monetized GHG emissions), while meeting the electricity load and systems constraints. Simulations were run to investigate how the operation of nine distinct storage technologies impacted system cost, given each technology’s characteristics. The results show that increasing the renewable capacity and the emissions tax would make it more cost-effective for energy storage deployment. Among storage technologies, pumped-hydro and compressed-air energy storage with lower capital costs, are deployed in more scenarios. Overall, this research demonstrates how sustainability performance is influenced by storage technology characteristics and the electric grid conditions. The systematic principles, model equations, and optimizations developed in this dissertation provide specific guidance to industry stakeholders on design and deployment choices. The targeted audience ranges from energy storage designers and manufacturers to electric power utilities.PHDNatural Resources & EnvironmentUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143942/1/marbab_1.pd

Distribution market as a ramping aggregator for grid flexibility support

The growing proliferation of microgrids and distributed energy resources in distribution networks has resulted in the development of Distribution Market Operator (DMO). This new entity will facilitate the management of the distributed resources and their interactions with upstream network and the wholesale market. At the same time, DMOs can tap into the flexibility potential of these distributed resources to address many of the challenges that system operators are facing. This paper investigates this opportunity and develops a distribution market scheduling model based on upstream network ramping flexibility requirements. That is, the distribution network will play the role of a flexibility resource in the system, with a relatively large size and potential, to help bulk system operators to address emerging ramping concerns. Numerical simulations demonstrate the effectiveness of the proposed model on when tested on a distribution system with several microgrids.Comment: IEEE PES Transmission and Distribution Conference and Exposition (T&D), Denver, CO, 16-19 Apr. 201

Emission-aware Energy Storage Scheduling for a Greener Grid

Reducing our reliance on carbon-intensive energy sources is vital for reducing the carbon footprint of the electric grid. Although the grid is seeing increasing deployments of clean, renewable sources of energy, a significant portion of the grid demand is still met using traditional carbon-intensive energy sources. In this paper, we study the problem of using energy storage deployed in the grid to reduce the grid's carbon emissions. While energy storage has previously been used for grid optimizations such as peak shaving and smoothing intermittent sources, our insight is to use distributed storage to enable utilities to reduce their reliance on their less efficient and most carbon-intensive power plants and thereby reduce their overall emission footprint. We formulate the problem of emission-aware scheduling of distributed energy storage as an optimization problem, and use a robust optimization approach that is well-suited for handling the uncertainty in load predictions, especially in the presence of intermittent renewables such as solar and wind. We evaluate our approach using a state of the art neural network load forecasting technique and real load traces from a distribution grid with 1,341 homes. Our results show a reduction of >0.5 million kg in annual carbon emissions -- equivalent to a drop of 23.3% in our electric grid emissions.Comment: 11 pages, 7 figure, This paper will appear in the Proceedings of the ACM International Conference on Future Energy Systems (e-Energy 20) June 2020, Australi

Applicability of thermal energy storage in future district heating system - Design methodologies and performance evaluations

District heating (DH) enables efficient and economical utilization of energy resources to satisfy the heat and hot water demands in buildings and is, thereby, well-established in Northern European countries. To achieve the future renewable energy system, the current DH systems are proved to undergo transitions towards the future DH systems, with major characteristics including renewable-based heat sources, low temperature networks, lower heating demands and smart controls. An important step is the coordination of heating and electricity sectors to achieve synergies and optimal solutions for the overall energy system, which is also known as the smart energy systems. Such goal could be achieved in a cost-effective manner by the flexibilities added from short-term thermal energy storage (TES) technologies. Despite the importance of TES has been demonstrated in previous studies, giving drastic changes compared to the current systems, the practical applicability of TES in the future DH systems remains unknown. The proposed benefits of TES might deviate from expectation considering the future characteristics, such as the low storage temperature levels and short space-heating period. Furthermore, the current studies about the TES applications have mostly focused on specific case studies. The findings are of limited applicability because they cannot be easily generalized and extrapolated to other future conditions. To explore the practical challenges and optimal applications of short-term TES units in the future, a systematic design framework that considers the diverse factors from top-level targets to bottom-level implementations is developed in this study. The top-level theoretical analysis method is developed to identify the load shifting potentials and associated storage capacities for the whole energy system, by comparing and matching energy supply and demand profiles. Compared to current bottom-up detailed system models, the proposed method requires only the energy profiles, which has resulted in much shorter analysis time. The method is further validated by complex system models, and because a good agreement has been achieved, it can be applied in various scenarios to efficiently pre-study the storage potentials. Then, the design of the practical TES capacity is derived from the theoretical result by considering performance indicators during realistic operations, such as power-to-heat conversion efficiency and heat loss efficiency.On bottom-level implementations, four typical short-term TES technologies were investigated including central water tank (CWT), district heating network inertia (DHNI), domestic hot water tank (DHWT), and building thermal mass (BTM). For this purpose, an integrated bottom-level model to simulate the operation dynamics of the district heating systems and to optimize the use of the TES units is developed. Techno-economic analysis and comparisons of TES technologies were performed on a variety of scenarios, which are representatives of the main characteristics of the current middle-temperature district heating system and future low-temperature district heating system. The changes in the source side, transportation networks and end-use building demands are considered. As a result, a performance map of the TES technologies indicating the strong links between the system characteristics and optimal TES applications has been identified. Based on that, the optimal combinations of TES technologies were proposed for a LTDH system. Consequently, combining this with top-level methods, the overall potentials and roles of short-term TES were identified by a systematic design framework

Challenges to the Integration of Renewable Resources at High System Penetration

Successfully integrating renewable resources into the electric grid at penetration levels to meet a 33 percent Renewables Portfolio Standard for California presents diverse technical and organizational challenges. This report characterizes these challenges by coordinating problems in time and space, balancing electric power on a range of scales from microseconds to decades and from individual homes to hundreds of miles. Crucial research needs were identified related to grid operation, standards and procedures, system design and analysis, and incentives, and public engagement in each scale of analysis. Performing this coordination on more refined scales of time and space independent of any particular technology, is defined as a “smart grid.” “Smart” coordination of the grid should mitigate technical difficulties associated with intermittent and distributed generation, support grid stability and reliability, and maximize benefits to California ratepayers by using the most economic technologies, design and operating approaches